Performance Assessment and Mathematical Modeling of Process Parameters in Electrical Discharge Machining of EN-31 Tool Steel Material Using Taguchi DOE

In non-traditional machining, electrical discharge machining (EDM) has tremendous potential on account of versatility of its applications and is successfully, commercially used in modern industries. EDM process is capable to machine geometrically complex, hard material components, tool steels, composites, super alloys, ceramics and carbides. In EDM, Material Removal Rate (MRR) and Tool wear rate (TWR) are generally analyzed to assess its performance. For this, a perfect combination of input variables is required. In the present study, machining is done on Tool steel workpiece material using a pure copper electrode. The input parameters like Pulse-ON time, Pulse- OFF time, Current and Gap voltage are selected for experimentation and Taguchi method is employed for the DOE by considering 4 factors and 3 levels. A total of 27 experiments (L27 orthogonal array) have been designed with a possible combination of selected input parameters. The present work mainly focuses on development of an extensive mathematical model for correlating the input and output variables using a conventional regression analysis. The adequacy of proposed model was tested with the help of some collected data through experimentation using taguchi optimized DOE. The proposed linear multi-variable regression equation was found to be a best fitted model with 98% confidence levels.In non-traditional machining, electrical discharge machining (EDM) has tremendous potential on account of versatility of its applications and is successfully, commercially used in modern industries. EDM process is capable to machine geometrically complex, hard material components, tool steels, composites, super alloys, ceramics and carbides. In EDM, Material Removal Rate (MRR) and Tool wear rate (TWR) are generally analyzed to assess its performance. For this, a perfect combination of input variables is required. In the present study, machining is done on Tool steel workpiece material using a pure copper electrode. The input parameters like Pulse-ON time, Pulse- OFF time, Current and Gap voltage are selected for experimentation and Taguchi method is employed for the DOE by considering 4 factors and 3 levels. A total of 27 experiments (L27 orthogonal array) have been designed with a possible combination of selected input parameters. The present work mainly focuses on development of an extensive mathematical model for correlating the input and output variables using a conventional regression analysis. The adequacy of proposed model was tested with the help of some collected data through experimentation using taguchi optimized DOE. The proposed linear multi-variable regression equation was found to be a best fitted model with 98% confidence levels